# The Role of Heterogeneity in Autonomous Perimeter Defense Problems

arXiv: https://arxiv.org/abs/2202.10433 · HTML: https://mlsanity.com/paper/2202.10433/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 21 Feb 2022.

## Built on by (most cited first, 2 of 2)

- [A Decentralized Spike-based Learning Framework for Sequential Capture in Discrete Perimeter Defense Problem](https://mlsanity.com/paper/2305.16748/) (2023)
- [Embedded Mean Field Reinforcement Learning for Perimeter-defense Game](https://mlsanity.com/paper/2505.14209/) (2025)

## Abstract (arXiv)

When is heterogeneity in the composition of an autonomous robotic team beneficial and when is it detrimental? We investigate and answer this question in the context of a minimally viable model that examines the role of heterogeneous speeds in perimeter defense problems, where defenders share a total allocated speed budget. We consider two distinct problem settings and develop strategies based on dynamic programming and on local interaction rules. We present a theoretical analysis of both approaches and our results are extensively validated using simulations. Interestingly, our results demonstrate that the viability of heterogeneous teams depends on the amount of information available to the defenders. Moreover, our results suggest a universality property: across a wide range of problem parameters the optimal ratio of the speeds of the defenders remains nearly constant.